Automated Organization Profile

Institute of Urban Environment

Current S-Index

65.4

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.3

Average Dataset Index per dataset

Total Datasets

50

Total datasets in this organization

Average FAIR Score

71.5%

Average FAIR Score per dataset

Total Citations

16

Total citations to the organization's datasets

Total Mentions

0

Total mentions of the organization's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Environmental and plankton time series (2010-2022) during recurrent cyanobacterial blooms from two subtropical reservoirs in China (Version: V1)

This database presents a 13-year dataset (2010–2022) from two adjacent subtropical reservoirs (Shidou and Bantou) in Xiamen, Fujian Province, Southeast China. It provides a quarterly overview of key statistical characteristics of the time series, including physicochemical parameters, microscope-based phytoplankton, and DNA sequence-based bacteria and microeukaryotes.

Authors

  • Shuzhen Li ;
  • Huihuang Chen ;
  • Jin, Lei ;
  • Xiao, Peng ;
  • Yang, Jun R ;
  • Zjie Xu ;
  • Lemian Liu ;
  • Yang, Jun
0 Citations0 Mentions69% FAIR0.5 Dataset Index
10.57760/sciencedb.280812025

NTL_PAI experimental data and code

The dataset is the raw data and experimental results of manuscript "Scale effects of the spatiotemporal relationship between nighttime light and population activity intensity: A case study in Shanghai, China".

Authors

  • Guo, Xiangzhong
1 Citation0 Mentions79% FAIR0.8 Dataset Index
10.5281/zenodo.170596972025

NTL_PAI experimental data and code

The dataset is the raw data and experimental results of manuscript "Scale effects of the spatiotemporal relationship between nighttime light and population activity intensity: A case study in Shanghai, China".

Authors

  • Guo, Xiangzhong
0 Citations0 Mentions79% FAIR0.5 Dataset Index
10.5281/zenodo.170596962025

Virome and microbiome in dust (Version: V1)

To explore the impacts of human disturbance and urbanization on airborne microbiome and virome, settled dust (B)and dust samples (A)were respectively collected from the rural, suburban, and urban areas of Xiamen (24°26′46″N 118°04′04″E), Fujian province of China. The settled dust was collected from the least-handled surfaces, which are minimum 1.5 m above floor level. Meanwhile, the dust sample was collected from the impervious surface nearby the settled dust sampling site. About 50 g of settled dust or dust were collected in each site and filtered through a 10-mesh sieve to discard stones and debris. The microbial and viral DNA were extracted from the sieved duts and settled dust, and sequencing on a Novaseq 6000 platform.

Authors

  • Li, Hu ;
  • Jianqiang, Su
0 Citations0 Mentions69% FAIR0.4 Dataset Index
10.57760/sciencedb.290412025

Vectorized Agrivoltaics Dataset in China (Version: V2)

Agrivoltaics is a farming method that strategically integrates solar panels with agricultural production, a dual-use system that boosts food production while generating clean energy. China is the one of leading countries in agrivoltaics. However, no robust vectorized dataset has been available to verify the distribution of agrivoltaics in China. This study aims to provide the first nationwide agrivoltaics distribution and type dataset in China using comprehensive identification methods based on published spatial data of photovoltaic power stations and agrivoltaics records. The overall accuracy of agrivoltaics through visual examination is 89.71%. The results show that: (1) By 2022, there are 1,678 agrivoltaics projects in China with a total installation capacity of 134.55 GW. (2) China launched its first commercial agrivoltaics in 2010, reaching a peak of 347 projects in 2017, after which the number of new agrivoltaics projects has remained no less than 140 annually. (3) The three most common agrivoltaics types are crop-based, fishery-based, and greenhouse-based. This vectorized agrivoltaics dataset will support macro-level management and the sustainable development of agrivoltaics.

Authors

  • Xueyan Zhang ;
  • Ma, Xin
1 Citation0 Mentions69% FAIR0.8 Dataset Index
10.57760/sciencedb.262402025

16S rRNA and ITS sequencing raw data of indoor dust (Version: V1)

16S rRNA and ITS sequencing raw data of indoor dust

Authors

  • Lu, Long ;
  • Qiansheng, Huang
0 Citations0 Mentions69% FAIR0.4 Dataset Index
10.57760/sciencedb.255892025

Metagenomic sequencing data of five earthworm guts and nine farmland soil samples (Version: V2)

The samples were collected at a long-term monitoring station managed by the Fuyang Agricultural Bureau in Zhejiang Province, China. Soil (samples S1-S9) and earthworm (samples E1-E9) samples were collected from the surface (5-15cm). The numbers 1-3 in the sample name indicate no fertilizer control; The numbers 4-6 represent chemical nitrogen (N), phosphorus (P), and potassium (K) fertilizer treatments; The numbers 7-9 represent treatments that combine chemical fertilizers (NPK) with commercial organic fertilizers In addition, due to insufficient DNA concentration, samples E1 and E5 were excluded from sequencing; Samples E7, E8, and E9 were merged into a library named E789.

Authors

  • cui hong xia ;
  • Hu, Liao ;
  • Jianqiang, Su
1 Citation0 Mentions69% FAIR0.6 Dataset Index
10.57760/sciencedb.245712025

glacial foreland metagenomes 202109 (Version: V2)

glacial foreland metagenomes 202109

Authors

  • Liao, Hu ;
  • Su, Jian-Qiang
0 Citations0 Mentions69% FAIR0.4 Dataset Index
10.57760/sciencedb.242082025

Dataset for "A Function-Driven Single-Cell Approach to Unveiling and Cultivating Hidden Microplastic-Degrading Microbes from Insect Gut Microbiota" (Version: V1)

Biodegradation is a sustainable strategy to address global microplastics (MPs) pollution but is constrained by the lack of efficient degrading microbes and effective tools to harness them. Here, we developed a function-driven single-cell approach to precisely identify and recover MPs-degrading microorganisms from complex microbiota by integrating isotope-labeled single-cell Raman spectroscopy with targeted cell sorting, sequencing and culturing. Using heavy water and MPs as the sole carbon source, Raman spectroscopy effectively identified active microbes capable of degrading multiple types of MPs from insect gut microbiota. Raman-guided single-cell sorting and sequencing revealed seven previously unrecognized polystyrene degraders and mapped key enzymes involved in each degradation stage. Furthermore, live-cell Raman-guided sorting enabled the cultivation of rare but highly active polystyrene degraders often missed by conventional methods. This “screen-first, culture-second” single-cell approach offers a powerful and scalable platform to accelerate MPs biodegradation and supports the development of microbial solutions to mitigate global plastic pollution.

Authors

  • Guo, Hong-Qin ;
  • Yang, Kai ;
  • Xing, Xin-Yu ;
  • Yang, Yu-Nan ;
  • Long-Ji Zhu ;
  • Kang, Xiao-Xi ;
  • Ju, Feng ;
  • Ji, Rong ;
  • Corvini, Philippe Francois-Xavier ;
  • Yong-Guan Zhu ;
  • Cui, Li
0 Citations0 Mentions69% FAIR0.4 Dataset Index
10.57760/sciencedb.243932025

Older lineages of oribatid mites in mountain ranges have broader geographic ranges and exhibit more generalistic traits (Version: 16)

Understanding ecological and evolutionary mechanisms that drive biodiversity patterns is important for comprehending biodiversity. Despite being critically important to the functioning of ecosystems, the mechanisms driving belowground biodiversity are little understood. We here investigated the radiation and trait diversity of soil oribatid mites from two mountain ranges, i.e. the Alps in Austria and Changbai Mountain in China, at similar latitude in the temperate zone differing in formation processes (orogenesis) and exposed to different climates. We collected and sequenced soil oribatid mites from forests at 950 to 1700 m at each mountain and embedded them into the chronogram of species from temperate Eurasia. We investigated the phylogenetic age of oribatid mites and compared the node age of species with the mountain uplift time of the Alps and Changbai Mountain. We then inspected trophic variation, geographical range size and reproductive mode, and identified traits that promote oribatid mite survival and evolution in montane forest ecosystems. We found that oribatid mites on Changbai Mountain are phylogenetically older than species in the Alps. All species on Changbai Mountain evolved long before the uplift of Changbai Mountain, but some species in the Alps evolved after the orogenesis of the Alps. On Changbai Mountain more species possess broader trophic variation, have larger geographical range sizes and more often reproduce via parthenogenesis compared to species from the Alps. Species on Changbai Mountain survived the mountain uplift or colonized the mountain thereafter supporting the view that generalistic traits promote survival and evolution in phylogenetically old soil animal species. Collectively, our findings highlight that combining species traits and phylogeny allow deeper insight into the evolutionary forces shaping soil biodiversity in montane ecosystems.

Authors

  • Pan, Xue ;
  • Heimburger, Bastian ;
  • Chen, Ting-Wen ;
  • Lu, Jing-Zhong ;
  • Cordes, Peter Hans ;
  • Xie, Zhijing ;
  • Sun, Xin ;
  • Liu, Dong ;
  • Wu, Donghui ;
  • Scheu, Stefan ;
  • Schaefer, Ina ;
  • Maraun, Mark
1 Citation0 Mentions77% FAIR0.8 Dataset Index
10.5061/dryad.2bvq83bz02025